Hey you.

Yes, you. Want to come work for Splitwise?

Splitwise is hiring its first full-time Data Scientist! At Splitwise, you’ll help us analyze data about our applications to discover key insights about user behavior. This work will drive future product decisions and inform Splitwise’s product roadmap. The most important product and business decisions we make at Splitwise have always been informed by what we learn from our users. With your help, we can improve Splitwise for our millions of users around the world.

Splitwise is a large consumer app that handles many millions of interactions per day. Using a combination of analytical thinking and statistical rigor, you’ll unpack that data to learn more about how people use Splitwise and why, and pass on that knowledge to our product and engineering teams to help them monitor changes, investigate key questions, and make better decisions.

Typical work for this role will include a mix of Business Intelligence reporting (cohort-based analyses of engagement and retention), ad-hoc observational product research (“how often do people settle debts and why?”) and statistical inference / experiments (ex: A/B tests). There may also be some opportunity for Data Science algorithm-based projects, but this will not be the initial focus of your work.

This job reports to the CEO, Jon. You’ll collaborate with engineers to ensure that our data pipeline works smoothly and efficiently, and collaborate with product managers and designers to inform future development. We’re a small team of about 10 people, and we’re excited to have you join us!

Communicate your findings to teammates to help them make informed product and technical decisions

Things about you:

You have past work experience in an analytical role on a Growth, Marketing, or Product team.

You have very strong quantitative and analytical skills, and a good working grasp of statistics (and the ability to learn in areas where you aren’t an expert).

You can use SQL to query a database and dig into crosstabs to answer tricky questions.

You have some ability to program basic scripts for running data analyses (language doesn’t matter so much).

You have strong collaboration skills. You can work with product managers, designers, software engineers, and business leaders on both technical issues (data pipeline problems or query performance) and non-technical issues (user personas or business impact).

You care about your work for its practical impact and who it helps – not just research for its own sake, or trying the latest new tools or buzzwords.

You highly value intellectual honesty with your peers, and prefer to be transparent and apolitical about the strengths and weaknesses of your research and possible interpretations.

You're willing to come join us at our office in Providence, RI. (If you're not from around here, we can help you move!)

You have a 4-year Bachelor's degree in Statistics, Applied Math, Computer Science, Physics, Economics, Chemistry, Biology, Neuroscience, or another quantitative field, or equivalent

Valued but not required: experience at a large consumer technology company, advanced statistical expertise, a relevant Masters or PhD, big data experience, software engineering experience, a machine learning background, a cool or impactful data science project you can share with us

Things you’ll learn:

How to best empower data-hungry teammates who need to answer their own questions

How to take a messy real-world product question and find concrete data to help answer it

How to build a data science dashboard that becomes a critical part of business operations

How to make product design decisions through a mix of qualitative and quantitative evidence and research

How a small, transparent start-up operates

We are an equal opportunity employer that cares deeply about diversity in tech, and we strongly encourage candidates from all backgrounds. We want to build a team at Splitwise that reflects the real world. We hope that team includes you!

Splitwise serves millions of users of all different ages and backgrounds in 170+ countries, and has raised money from leading investors in San Francisco, Boston, and New York. Join us in our mission to reduce the stress that money places on relationships, and help millions of friends and families around the world.